Operations | Monitoring | ITSM | DevOps | Cloud

Agentic, autonomous ITOps improves incident response by carrying context from detection through resolution, reducing noise, delay, and manual coordination. Most IT incidents don’t fail due to missing data. Monitoring systems generate more than enough signals. The problem is that understanding those signals—and deciding what to do with them—happens in fragments. Engineers move between dashboards, logs, tickets, and chat threads, stitching together context by hand.

Moving quickly is essential for modern engineering teams, but speed without guardrails can introduce hidden risks in testing. As organizations scale, teams often define and apply coverage standards inconsistently across services and repositories. What qualifies as “acceptable coverage” in one project may be completely different in another. Without automated enforcement, untested code can slip through reviews.

As codebases grow across many different services, it becomes harder to see what test suites actually cover. AI-assisted development and faster release cycles increase the volume of changes landing in repositories, raising the risk that untested code will make it through to production. To maintain a high standard, teams need clear and scalable visibility across repositories, consistent testing standards, and a way to catch blind spots before they reach users.

If you’re using AWS Bedrock, AWS can use your data for model improvement by default. VPC endpoints do not prevent this. You need to explicitly opt out inside AWS Organizations. It takes 2 minutes, and in this blog I’ll show you how.

ilert now supports a native WhaTap integration, connecting AI-native observability with AI-first incident management in a seamless workflow. This integration allows DevOps, SRE, and IT teams to move instantly from detection to resolution – cutting through alert noise, improving coordination, and dramatically reducing MTTR in even the most complex IT environments.

Modern data centres are hitting a wall that faster CPUs alone cannot fix. As workloads scale out and latency budgets shrink, the impact of moving data between servers is starting to become the most significant factor in overall performance. Remote Direct Memory Access, or RDMA, is one of the technologies reshaping how that data moves, and it forces a rethink of some long-held assumptions in data centre networking. This article is the first in a short series.

With all the discussion in the dev community lately about changes made at Heroku, we wanted to use this moment to talk about PaaS (Platform as a Service) providers and how AppSignal can be a vital tool to ensure you're using your app's hosts for everything from optimal performance to lower usage bills.

A lot of talk around OpenTelemetry has to do with instrumentation, especially auto-instrumentation, about OTel being vendor neutral, being open and a defacto standard. But how you use the final output of OTel is what makes business difference. In other words, how do you use it to make your life as an SRE/DevOps/biz person easier? How do you have to set things up to truly solve production issues faster?

Today we're announcing that Sentry has acquired XcodeBuildMCP, an open source MCP server that gives AI agents the ability to build, test, and debug native iOS and macOS apps. XcodeBuildMCP has become a go-to tool for agentic Apple-platform development, with more than 4,000 GitHub stars and an active community. It unlocks the full developer loop: build, run, debug, interact, and verify, allowing users to stay in their preferred agentic development environment.

The market is saturated with agents and assistants, making it difficult to tell them apart. However, the difference between these two approaches is significant. They offer radically distinct levels of impact, reflecting major differences in both their technical complexity and the quality of their inferences. Let’s figure out the distinction.